AI Writing Pattern Checker
Explore English writing patterns locally. The underlying RoBERTa detector was trained on GPT-2 outputs, not validated here for modern AI models. Load the model deliberately to begin; its score cannot establish authorship or publishability.
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Technical details
Results appear here after analysis.
How AI Content Detection Works
AI detectors analyze writing patterns. Rather than claiming that individual words are AI-generated, this tool highlights paragraphs or sections whose combined model and writing-pattern signals are elevated.
What the detector examines
- Sentence variation — Variation is descriptive, not evidence of who wrote a passage.
- Word predictability — The legacy model estimates patterns learned from its training data.
- Phrase repetition — Repeated phrases can suggest an editorial review, not an authorship conclusion.
- Lexical diversity — Range of unique vocabulary provides another signal.
- Section-level hotspots — Color coding shows where template markers, stock phrasing, or elevated model scores are concentrated.
Best Practices
Use as one signal
Pair the score with your own review.
Context matters
AI-pattern scores matter differently depending on content type.
Respect uncertainty
Trust mixed results rather than forcing a decision.
FAQ
Tool notes · Reviewed Jun 2026 · Sources and limitations
Review details: 2026-06-13 · Marc LaClear · v1.3-beta
Reference sources:
- Transformers.js docs
- ONNX Runtime Web docs
- WebGPU spec (W3C)
- OpenAI / RoBERTa detector model card
- OpenAI text classifier limitations
Known limits:
- AI detection is probabilistic and can be wrong.
- The deployed manifest identifies roberta-base-openai-detector (GPT-2 output detector), wrapper version 1.2, with writing-pattern overlay 1.1.0. The overlay has no published benchmark or calibration.
- Color coding highlights paragraph- or section-level evidence only; it does not prove that specific words were generated.
- Accuracy varies by text length, domain, author style, and AI model.
- Edited AI text and non-native English may produce uncertain results.